5 1 Introduction Following Barua, et al. (1999), OECD (1999a), and Mesenbourg (1999), defining and measuring the economically relevant impacts of internet activities remains an open issue. In particular, this is seen to apply to the development of "e-commerce". There exist various measures of business-to-business and business-to-consumer trade in common goods and services. However, according to all recent policy reports - such as US Department of Commerce (1999), OECD (1997; 1999b, ch. 1), and the Gemini (1999) study initiated by the European Commission, for instance - the respective social product contributions must currently be viewed as insignificant. Hence, estimates of the percentage of internet mediated sales in total retailing value range between less than 1 % [US Department of Commerce (1999)] and less than 0.5 % [OECD (1999b, p. 27) for seven countries]. Moreover, Gemini (1999, p.l) expects the impact of such internet activities on the European economies' domestic products and labor markets to remain " relatively small" for the next five years. Policy reports therefore rather emphasize the extreme growth rates realized in this sector. Furthermore, the studies generally agree in predicting significant spill-over effects fostering general economic growth. OECD (1999b) thus expects the value of e-commerce activities to grow from $ 26 billion in 1997 to $ 330 billion in and $ 1 trillion in Most recent figures by Internet Economy Indicators (1999) - a detailed description of which can again be found in Barua, et al (1999) - estimate that commercial internet revenues experienced 127 % growth between 1998 and They already account for 26 % of the $ billion total revenue generated in the so-called "internet economy". The respective 78 % employment growth in e-commerce also well exceeds the 46 % industry average. In 1999, 900,882 employees in commercial internet firms constituted 39 % of total internet related employment. This compares to 28 % employed in structuring and maintaining the technical infrastructure, 24 % in internet software design and consultancy, and 19 % in the provision of intermediation services such as search engines, electronic brokerage, and auctioning. Thus, e-commerce will "expand existing markets and even create new ones" [US Department of Commerce (1999, p. 10)]. At the same time, it "can significantly influence existing market activities" [OECD (1997, p.'44)]. In particular, the "the longer-term viability of firms [...] vnll be determined by the strategies they choose to pursue [Gemini (1999, P- 1)1-

6 However, the internet economy has only begun to attract the attention of the economics discipline. Also, the existing literature almost exclusively focuses on the specific aspects of internet technologies, services, and products. The contributions collected in Kahin and Keller (1995) and McKnight and Baily (1997) thus discuss the volume and structure of internet communication, problems of congestion pricing, tariffs for internet services, and the distribution of internet access over the population. Even marketing studies - unambiguously market and strategy oriented - are currently entirely confined to investigating the impacts of internet technology on consumer and supplier behavior. The pace and unpredictability of technological change then either precludes the possibility of projecting future developments as in Peterson, et al. (1997), or inspires conceptual ideas concerning the design of the future net environment in Hoffman and Novak (1996). Hence, despite the obvious business and public interest, analyses of the interdependencies between traditional and new internet markets are generally lacking. Clearly, internet technology and services alter the search behavior of potential buyers. Thus, Hoque and Lohse (1999) demonstrate that successful consumer search implies different strategies and costs in traditional and internet "yellow pages". Moreover, policy reports [US Department of Commerce (1999, p ), Gemini (1999, p.13, 17-18), OECD. (1997, p. 6; 1999b, ch. 2)], economic analysis [Zerdick, et al. (1999, p ), Choi, et al. (1997, Ch. 7)], and marketing studies [Alba, et al.(1997)] agree that internet technology reduces search costs. Suppliers, internet operators, and specialized service firms invest significantly in the provision of efficient search means. Software programs which operate as agents of the consumers scan all available information concerning prices and quality attributes of internet offers. Such "shopbots" - analyzed by Kephart and Greenwald (1999), Greenwald and Kephart (1999), and Greenwald, et al. (1999) - increase the price elasticity of demand. Further, in addition to the "globalization" effect, competition among firms is also enhanced by new "nonindustry" entrants [OECD (1999b, p )]. Consequently, internet trade should increase consumer surplus [Bakos (1997)]. This obviously raises the question whether traditional markets may remain viable at all. Given the technological development, respective approaches emphasizing the transaction costs of entering internet.and traditional markets appear myopic. However, the existing internet economics literature also provides some hints concerning the possible longer-term limits of market substitution. Hence, Greenwald and Kephart (1999) and Greenwald, et al. (1999) already investigate the strategic interaction of

7 "shopbot" consumer and "pricebot" supplier agents in internet markets. The latter employ price-setting algorithms responding to the "shopbot" queries. Further, regulators worldwide - as summarized in US Department of Commerce (1999), Gemini (1999) and OECD (1997) - currently attempt to achieve a balance between supporting the development of the internet economy and consumer protection. They express significant concerns associated with the security and privacy of e-commerce transactions, as well as domain name identification and quality standards for sellers. Finallly, Choi, et al. (1997, ch. 8) and Kalakota and Whinston (1999) emphasize that successful internet marketing necessarily requires increased differentiation of suppliers and products. In particular, firms must pick an appropriate mix of market segments. In summary, these arguments suggest that e-commerce provides dominant search means as far as standardized product and price information is concerned [Bakos (1997)]. However, given the sellers' or product characteristics such standardization may not be possible. Zerdick, et al. (1999, p ) and Choi, et al. (1997, ch. 5) point out that the usual adverse selection problem is reinforced by network economies. Further, the information provided by suppliers pursuing a differentiation strategy - as illustrated by Choi, et al. (1997, ch. 6) - obviously rather deters the possibilities of comparing offers. Hence, some information cannot, or will not be communicated verifiably. The analysis of market substitution and interaction must therefore explicitly distinguish product or agent information which can be gathered more efficiently via the internet from quality signals which remain private information. Choi, et al. (1997, p. 169) therefore conclude that the future of the internet "may depend on how non-technological but fundamentally economic issues as the lemons problem are solved". Bakos' (1997) analysis of electronic marketplaces already demonstrates that lower search costs may restore, or improve equilbrium trade which is subject to quality uncertainty. However, the current model specifically addresses the issue of market substitution. It demonstrates that, if adverse selection cannot be eliminated completely, internet and traditional markets may co-exist. The analysis draws on standard adverse selection theory. However, it also introduces a risk reducing, but not eliminating linear learning process. The costs of gathering informative quality signals then vary between marketplaces. Nevertheless, an equilibrium with parallel markets or market segments may exist, if the migration of sellers reduces the adverse selection problem in the market characterized by higher information costs. While the migration process between markets - hence, the evolutory dynamics - cannot be modelled, the

8 equilibrium is robust with regard to both seller and buyer incentives. The analysis thus also contrasts with approaches exclusively emphasizing the dynamic aspects of internet market emergence. Obviously, the formal model combines well-known pieces of economic theory. Nevertheless, the empirical application to trade in used-cars pursued in section 3 does not only reflect an interest in testing Akerlof's (1970) seminal work on the "lemon market". The quality of a used car is determined by investments of both original manufacturers and current owners in technical reliability. However, the maintenance effort of the latter'remains private information. In addition, the typical spot-market characteristics preclude formal warranty or "money back" agreements as discussed in Choi, et al. (1997, Ch. 4). Hence, in many respects the used-car market - although predominantly involving consumer-to-consumer-trade - provides a prime example for investigating the impact of private seller information on retailing in experience goods. E-commerce activities then only provide an alternative means of exchange [Bakos (1997), Keeney (1999)]. Furthermore, internet trade is already well-developed in both the classified ads and automotive businesses. According to the US Department of Commerce (1999, p. 10), Gemini (1999, p. 21), and OECD (1999b, p. 44, 48), this implies a significant degree of market substitution. As a by-product, classified ads for used cars therefore allow to compile data for empirical analysis. 2 A model framework 2.1 Quality and information structure Given the empirical application ^to follow, the analytical discussion will be framed within the terms of the used car market. The quality of a used car reflects the value of transportation services minus repair and maintenance costs incurred by its future owner. Formally, let qg denote the quality of a car in the possession of current owner I. Then, q e = q(a, y) + p e + e (1) where q(a, y) captures the quality effects which are associated with car-type reflects the maintenance effort and ability of its current owner. More precisely, a. constitutes a deterministic vector of car characteristics. This list includes brand name and model type, horse-power, size of engine, but - where

9 applicable - also the accessory units such as air-conditioning, sun-roof, etc. The vector y then contains signals concerning the car's current state of attrition which are related to the original manufacturer's investments in protection against the average wear and tear. Given the present application, age, mileage, and mileage per year since first licensing constitute typical y-entries - the latter easily calculated from the first two entries. While high age and mileage are certainly "bad news" as far as expectations about future reliability and repair costs are concerned, the third is usually considered to be positively correlated with qg. High realizations of mileage per year indicate less time spent in the stop-and-go-traffic of cities and more freeway driving. There further exists an owner-determined quality effect associated with the individual decisions to invest in car maintenance. In accordance with Akerlof (1970), /3 e constitutes perfectly private information of the current owner. In fact, this variable captures all owner-determined quality enhancing activities which cannot be communicated verifiably to potential buyers. e is assumed to be independent of {a,y). Thus, potential buyers believe that owner-determined quality constitutes the realization of a random variable (3 which is distributed according to H((3) over the population of current owners. Following Akerlof's (1970) original study and common textbook examples - i.e., Milgrom and Roberts (1992, p ) and Campbell (1995, p ) - on adverse selection models, H{f3) is taken to be uniform with /? [0,/? H ]. Finally, s denotes a random variable reflecting the stochastic nature of the impacts of both the original manufacturer's and the current owner's investments on realized car quality. For simplicity e ~ N(0,cr 2 ). The information concerning a and y is communicated via the advertisement placed by owners. In this respect, the used car market found in the classified ad sections of newspapers, but also in the internet has established a market standard. All elements of a and y can be easily verified on eyesight inspectation by a potential buyer. Thus, the analysis excludes the possibility "of fraudulent offers associated with deliberate manipulations of the speedometer or title documents by the current owner. However, there also exists a second set of signals concerning qg. Hence, motorist clubs and automobile magazines perform endurance and comparative driving tests. They may also provide information concerning typical repairs and statistical information on repair frequency and average repair costs. Similar information may be available from the original manufacturer, or still other sources. In the following, let Ig denote the cardinality of the vector z\ containing such additional signals concerning q\ which are

10 known to the current owner. For simplicity, z o t is assumed to constitute a "complete" signal vector. Current owners have collected all test and other available information concerning the car which has been in their possession over the past years. This implies Zg = z for all owners i. It then further appears plausible that / = I(a,y). Obviously, more test, endurance, and repair statistics are collected and published as the car ages. Also, certain brands may receive more public attention than others. Every element z it g, i = 1,..., I(a, y), is taken to satisfy, Zijt = qg + r)i (2) where % is normally distributed with expected value zero and identical variance 2, for all i = 1,...,I(a,y). Furthermore, cov^^n^ = 0, for all j ^ i, and cov{e,n i ) = 0, for all i = l,...,i(a,y). Kirby (1993) has already introduced linear Bayesian learning in order to model market processes of merging and separating information pools consisting of signal vectors. Within the current framework this approach allows to distinguish potential buyers' and sellers' expectations concerning product quality. Hence, following De Groot (1970), q c is then distributed normally with expected value and variance E[qg\z }=q(a,y)+/3g (3) Var[qg\r] = + ^J" 1 ' (4) from the point of view of a current owner. In contrast, potential buyers 'must engage in costly information gathering activities in order to obtain a signal vector z b m(c\,y) of cardinality J m (a,y) = ^(a,f/). The information costs are assumed to be given C m (a,y) = CmJ^a,^). Subscript m, m = {iv, M}, identifies the specific market in which these research activities take place - the internet or the traditional print media classified ad market, respectively. Signals are thus generally perceived as single information units which can be gathered at constant unit costs. Potential buyers must either actively engage in market research or receive the information via communication with current owners prior to purchasing the car. The unit costs of information gathering assumed to be independent depend of whether signals are obtained by own research or communication. Yet, the two market

11 places differ with respect to the distribution of these costs between the two parties. Thus, 7 m,to = {N, M}, denotes the share of total information costs incurred directly by the potential buyers. Intuitively, / y m C m (a,y) then reflects the costs of market research by potential buyers, while (1 7 m )C m (o;, y) can be associated with the costs of communicating signals which are incurred by current owners. This interpretation appears particularly plausible, since current owners must ensure that information is communicated verifiably to potential buyers. According to Bakos (1997), lower search costs in the electronic marketplaces are mainly associated with gathering price information. The argument is not extended to non-standardized products, or seller information, however. Thus, consider a potential buyer responding to ads in the traditional print media market. Researching on its own the individual will have to scan all relevant publications by motor clubs, manufacturers, etc. Very likely, he will also have to purchase single issues of magazines or test reports. On the other hand, internet shopping implies that - given an initial fixed fee and variable costs which are only related to the duration of the research activities - additional signals can be obtained using the net itself. Providers also supply search machines or "shopbots" for assistance. Yet, the verification costs associated with electronic communication are commonly regarded as relatively high. The internet provides a larger signal pool at the expense of allowing offers into the market without exercising significant filtering. These arguments justify the following assumptions: First, CN < Cu captures the general information cost advantage of internet shopping. At the same time, IN > 1M reflects the less severe verification problem in communicating information associated with the traditional print media market environment. Thus, potential buyers in the internet engage in more market research on their own. Clearly, rational buyers engaging in market research will ensure not to collect signals twice. Merely for illustrative reasons suppose that current owners were able to communicate their type (3 e as well. Then, if a potential buyer in markettohas received the signal vector z^(a, y) consisting of J m (a, y) signals, E[qg\z b m{a, y)) = q(a, y) + f3 e = E[qt\z \. However, the variance equals Var[q e \z b m(a,y)} = [± + ^ii^-i, m = { N:M } (5) Obviously, J m (a,y) < I(a,y) therefore implies that potential buyers are less informed about the technical quality than current owners - even ignoring the owners' private information concerning their investments in car maintenance. The possible

12 information gap defined by (4) and (5) thus induces an additional risk differential concerning technical reliabilty. Finally, despite the fact that potential buyers actually collect discrete signals, (5) is taken to be differentiable in J m throughout the following analysis. Note that - as far as the respective stochastic impacts on a used car's quality are concerned - the original manufacturer's and the current owner's investments in reliability are simply additive. Yet, potential buyers actually face two distinct sources of informational deficits relative to current owners. First, different sets of additional informative signals induce differences in the precision of forecasting the car's future value. Potential buyers are able to reduce this information gap by gathering costly, but informative signals, however. The second informational asymmetry arises due to the fact that owner-type information cannot be communicated verifiably at all. 2.2 Expected utility and information gathering The typical classified ad placed by current owners in the used car market contains the general car description (a, y) and a price for which the owner is willing to sell. Although adjusting to equilibrium different (a, y)-cax owners may advertise various prices, the analysis can be more easily followed by considering only equilibrium ads Am{&,y) = [Pm(&,y),a,y] in marketto.in the following, the advertised characteristics (a, y) will then be said to define segments of marketto. The empirical analysis cannot distinguish between prices contained in advertisements and the terms of actual exchanges. Consistency thus requires that the theoretical model to be developed entails trade triggered by the prices quoted in the advertisements. The instantaneous preference^ of all individuals meeting in both markets will be assumed to be characterized by identical exponential utility functions with constant degree of absolute risk aversion r > 0. Hence, focussing on the (a, y)-segment of market TO, an owner of type /3 will advertise his car, if -V s (a,y)exp{-rp e } < -exp{-r[p m (a,y) - (l-y m )C m (a,y)]} (6) where - exploiting the assumptions-above - V s (a,y) =exp{-r 1 (\ ~ 2 r { ^ Tt - -- NN " 1 + } (7)

13 The LHS of (6) contains the expected utihty of retaining the car, while the certain utility derived from the net reward of a sale is given on the RHS. Obviously, (6) - (7) determines a maximum owner-determined car quality offered, given the equilibrium price and the cardinahty of the information vector communicated in the (a, y)-segment of marketto. In particular, only owners characterized by (3 e < B m (a, y), where B m {a,y) = P m {a,y)-(l--y +IJ m )C m (a,y)-q{a,y) (8) PY are willing to offer their cars for sale. Potential buyers must incur the cost of market research. Thus, if purchasing a car in the (a, y)-segment of marketto,a buyers's expected utihty is given by B m (a,y) U m (a,y) = -t (fi,y) J ex V {-rp}[b m (a,y) - b m (a,y)}- l d0 (10) where ^ r[e + q{cc,y)-p m {a,y-)- lm C m {a,y) (11) As in Akerlof's (1970) original work, 6 > 0 induces the possibility of Paretoimproving exchange upon every random match of current owners and potential buyers, if both parties possessed identical information. It reflects the higher urgency of need associated with the non-owner status of an individual. Else, (10) differs from the conventional adverse selection model only in allowing for the possibility that some "poor quality"-owners - characterised e < b m (a,y) - may be absent in this particular segment of market TO. Focussing on (11), efficient information gathering in marketto obviously implies 1 JL(c\,v^~ 2 2 " C 2 c j (12) where J^(a,y) denotes the optimal activity level. In the following, it will be assumed that (12) implies an interior solution J^(a,y) = J^ < I(a,y) for all segments

14 (a, y) in both market environmentsto = {N, M}. Furthermore, irrespective of the particular means of information gathering - e.g., whether more signals are communicated or obtained by market research of potential buyers - the respective activity levels are always efficient relative to the particular market costs. This solution would obviously always be implemented by optimal market research decisions of potential buyers, if the number of signals actually communicated by current owners in each market does not exceed J^. Thus, let U^(a, y) denote the expected utility of a buyer in segment (a, y) of market TO given the efficient information gathering activity levels. The alternative for potential buyers always consists of not purchasing a car at all. Hence, if an (a, y)-segment attracts potential buyers in market TO, must constitute a necessary condition. U* m {a,y) >-I (13) 2.3 Equilibrium with parallel market segments Consider the internet market N first. If only this market exists, it is clear that bn(a,y) = 0. Given no possibility to sell in a different market, the gains of entering the used car market decrease with j3 - "low quality" owners benefit most from adverse selection. Provided that the segment (a, y) attracts potential buyers, (8) can then be rearranged to insert for PN(a,y) into (11). This yields with U* N (a,y) = -Vft(a,y) / exp{-rp}[b N (a,y)}-'df3 (14) Jo 4 V%(a,y) = exp{-r[6-b N (a,y)-c N J* N (15) The second line of (15) should be observed to contain the risk differential associated with the information gap between current owners and potential buyers. It is easily verfied that (14) is monotonically decreasing in B N (a>,y). The attracting of higher quality owners must be achieved by offering higher prices, which will always be attractive for low quality owners as well. Consequently, the adverse selection problem 10

15 for buyers will become more severe when the top quality offered in the market increases. Clearly, BN(a,y) > 0 also requires that 8 is sufficiently large in order to compensate the information gap between owners and buyers with regard to technical uncertainty. Suppose that the internet market involves active trade in more than one (a,y)- segment. In competitive equilibrium, (13) must then hold with equality for all such segments. This defines equlibrium values BN{&, y) for all segments which entail positive trade. However, differentiating (14) reveals that dbn(a,y)/di(a,y) < 0. When the information gap between current owners and potential buyers widens, prices and, thus, the top owner-determined car quality offered in the market segement must decrease. For a given value of 9, this implies that equilibrium prices pn(a,y) > 0 inducing BN(Q>, y) > 0 may not exist for all market segments (a,y). Trade will not occur in segments characterized by a large maximum number of available quality signals I(a,y). In such cases, the informational gap between car owners and potential buyers prevents bilateral beneficial trade in such cars. Next, consider only (a, y)-segments involving positive trade in the internet. Assume that there exists a parallel market based on the traditional classified ads in print media. Then, if trade occurs in the (a, y)-segment of this market, the following must clearly hold: P xr [ f \ 7 / 1 I I / *V,, l / ' v : /-mi- ~~ /""a /r I C\ 1/1 I 1 / V * * \ f i i / r l r I 1 n I In order to ensure positive supplies in both markets, the net rewards associated with a sale must be identical. Else, one of the two markets will attract all current owners in this segment. Inserting (16) into (8) then yields BN(a,y) = BM(&,y) = B(a,y). Identical rewards obviously imply an identical top-quality owner-type offering his cars. Utilizing this result and inserting from (8) in (10) thus yields rb(a,y) U^a^y) = V M (a,y) / exp{ rp}[b(a,y) 6^(0;, V)]~ 1 dp (17) with V M (a,y) = exp{-r[e-b(a,y)-c M J* M (18) Again, the risk differential in the second line of (18) is associated with the information gap between owners and buyers. It is easily verified that (17) is monotonically 11

16 increasing in bm{a,y)- While (16) ensures that current owners are indifferent between offering their cars in either market, U^(*,y) = U*t(a,y) = -l (19) must then additonally hold for all parallel (a, y)-segments in order to attract potential buyers. The first equation implies exp {-r [C N JN - c M J M ( 20 ) * a, y) - b M (a, Note that the second line on the LHS of (20) now contains the risk differential induced by the information gap between potential buyers in the internet and the traditional classified ad market, respectively. It reflects the different efficient information gathering activity levels in the two markets. The expected utility effect of increasing bm{ot-,y) above zero in the conventional print media market implies that (20) may be satisfied despite this information gap. In this case, let the equilibrium lowest value of owner-determined quality traded in the conventional market be denoted >M(a, y) > 0. Note that the LHS is constant for all such parallel market segments involving positive trade. This follows from the assumption of linear Bayesian learning combined with constant unit information costs. Then, differentiating the RHS reveals db{a,y)/db M (a,y) < 0. Thus, as the information gap 4 between potential buyers and current owners widens - yielding db(a, y)/i(a, y) < 0 as discussed above - the difference [B(a, y) l>m(a, y)] decreases. Yet, it cannot decrease beyond [B(a,y) 6jvf(a,y)] = 0 - due to (8) and (16). Otherwise all current owners would again move to only one market. Hence, parallel market segments with positive trade must be associated with relatively low values of I (a, y). The cars offered in such segments are characterized by relatively few additional signals concerning their technical reliability in the owner's information set. As more of such signals become available and known to current owners - thus, the increase in I(a, y) widens the information gap between current owners and potential buyers - [B(a, y) 1)M(C\, y)] converges to zero. Even higher values of /(a, y) then imply that such (a, y)-segments only exist in the internet market. Due to lower information 12

17 B&Ttothek Instifete ftr Weltwirtschaft costs, this market generally entails a smaller information gap between current owners and potential buyers. As shown above, for extreme I(a, y)-values positive trade may not be possible at all. Such segments cannot be found in either the internet or the conventional print media market. 2.4 Parallel markets and testable hypotheses Adverse selection equilibria exist due to the inobservability of quality signals in markets for experience goods. This obviously implies that - despite the "lemon" model's frequent inclusion in modern micro-economic textbooks - direct empirical tests can hardly be conducted. It appears implausible that the researcher is able to collect quality signals which cannot be observed by the agents in the market. However, Bond (1982) uses a maintenance cost survey on pick-up trucks which provides ex-post quality information. The study compares trucks bought new, respectively used by their current owners and controls for quality differences which can be communicated between buyers and sellers - hence, the ^-characteristics introduced above. Significant differences in the probabilities to require major repairs cannot be confirmed. Thus, trade in used pick-up trucks does not appear to induce an unobservable seller-contingent quality risk. The fact that used pick-ups did require more maintenance on average is attributed to " significantly higher lifetime mileage in each model year". This is seen to constitute "bad news" for potential buyers. As noted above, mileage per year may not constitute a monotone quality signal, however. Further, the analysis does not control for differences in brands and accessory units. Also, the pick-ups in the sample are predominantly used commercially. The respective buyers and sellers are therefore not typical agents in a "lemon" market. In contrast, the current empirical investigation uses data on traditional and e- commerce trade in used "family" cars. The occurrence of equlibrium parallel trade - in cars characterized by identical manufacturer specifications and advertised quality information - then provides an indirect test of the adverse selection hypothesis. Note that the equilibrium is in fact incentive-compatible. Obviously, the net rewards for current owners are equalized. Thus, potential sellers of (a,f/)-cars randomly select over the internet and the traditional classified ad market, if this segment exists in both markets. At the same time, potential buyers are indifferent with regard to shopping over all segments and markets. Hence, they also randomly select. Now, suppose that the buyers' information gathering activities are less costly in the internet. Then, only 13

18 if additional seller-contingent quality risk induces adverse selection, the internet will not strictly dominate the traditional market-place. In equilibrium the relatively higher costs of information gathering must be exactly compensated by less adverse selection in the traditional market. Two different sources of inefficiency are thus necessary in order to generate positive equilibrium trade in parallel market segments. In fact, this constitutes a standard result of second-best analysis [Lipsey and Lancaster (1956)]. Although the test of existing adverse selection is indirect, it necessarily only requires the assumption of competitive equilibrium between e-commerce and traditional trade. Disputing this assumption implies that parallel market places must reflect agent heterogeneity with respect to individual market-entrance costs. Consequently, market-entry decisions would be agent-specific and not contingent on advertised information signalling the attrition-state of the car. However, some segments may only exist in the market environment exhibiting lower information gathering costs for potential buyers. Very old cars may be considered as "oldtimers". These are highly valued by their individual owners and - if at all - sold in specific markets. More commonly, however, cars age until they possess only "scrap value". In part, the existence of scrap yards certainly reflects the elimination of trade due to the-information gap between potential buyers and sellers with respect to technical quality risk. Consequently, all used cars which are not scrapped must be traded in the market environment involving lower information gathering costs. The high information cost market will then lack some segments which - according the observable signals (a, y) - imply low quality. Thus, the assertion that internet trade is associated with lower information costs implies that such (a, y)-cars can be found in the internet, while not being advertised in the conventional classified ad market. Comparing the offer distributions between the two markets therefore allows to test the information dominance assertion for electronic trade without referring to prices. Despite lower search costs, additional mark-ups and risks associated with new intermediation services [OECD (1997, p. 9-10), Zerdick, et al. (1999, p )] and the necessity of intensified advertising in the pursuit of differentiation strategies [OECD (1999, p ), Choi, et al. (1997, p )] render price effects generally ambiguous. Applied to the classified ad market for used cars these arguments appear inadequate, however. First, the informational asymmetry is ultimately associated with an individual seller's personal characteristics in a spot-market environment. Second, the information communicated via classified ads is in fact identical in the two market- 14

19 places. Hence, lower information costs must be associated with lower prices unless consumers in the internet incur a smaller share of these costs. Yet, the e-commerce literature unanimously agrees that consumer search activities in the internet are more intense. Obviously, the development of "shopbots" and "chat groups" in which individual experiences can be communicated reflect an increased search activity level of the internet consumer. Empirically, Hoque and Lohse (1999) further support this assertion. Obviously, the characteristic model properties mirror the arguments found in the current descriptive literature on e-commerce. In particular, the model captures both the effects of search cost dominance and of a more severe selection problem associated with the new electronic marketplace. However, these views are not opposing - yielding either optimistic or rather sceptical scenarios concerning the future development of internet trade. In equilbrium both markets may co-exist. Such parallel markets can even continue to exist, if potential buyers augment the signal vector communicated in the traditional classified ad market by engaging in additional internet research. Only if the distribution of information costs, the information gathering means, and the respective activity levels are identically equal in both markets, trade must occur in a single market - characterized by identical prices for all (a, y)-cars advertised. 3 An explorative empirical investigation 3.1 Data description The empirical analysis focuses on internet and print media classified ads for Volkswagen Rabbits series III and BMW series 3xx. This brand and type combination has been chosen for two reasons. First, both vehicle types are very widespread in Germany. This allows to collect a sufficient number of observations in both marketplaces. More importantly, however, the general public as well as the automobile experts' interest in both brand models can be assumed to be equally developed in Germany. Also, VW and BMW representatives exist in virtually every German city. Second, the two model types do not constitute close substitutes from the point of view of potential buyers. BMWs rather appeal to auto-sports interested customers, while the VW Rabbit is a typical economy car. Including the brand variable in the analysis can therefore provide additional evidence with respect to model specification. The respective vectors of 15

20 addtional signals - denoted z in the analysis above - should possess approximately equal cardinality. Hence, if agents randomly select over marketplaces, this variable should not attain statistical significance in explaining differences in the probabilities of being offered in a particular market. At the same time, brand name should prove to exhibit price effects reflecting consumer preferences. Obviously, observations cannot be drawn from a complete, or representative sample of used cars traded in Germany. Moreover, the theoretical model rests on the existence of unobserved selection in the offer distributions. Thus, standard techniques to control for sample selection bias cannot be employed sensefully. It was therefore decided to minimize this problem by clustering the data sources. The researchers defined a number of regional and national newspapers to be searched for the respective classified ads. Internet pages were selected randomly. Further, the data collection was confined to classified ads which appeared in the second week of June Undergraduate students then compiled complete sets of offer observations within these pre-specified media and time-span. Nevertheless, the results reported in the following may still be subject to sample selection bias. Rather than providing a representative analysis, the current empirical investigation is therefore explorative in nature. Following this procedure, the empirical investigation can be based on a total of 449 observations for the two brands. Among these, 271 have been derived from newspapers. The data set contains 45 % BMW-observations in the traditional print media and 25 % respective internet entries. In the following regression analyses VW (BMW) then attains the value 1 (0). In addition to brand name, model type, and the price requested, the ads contain information concerning air conditioning, sun-roofs, air-bags for both front passengers, size of engine in 1000 cm 3, and horse power. Also, all ads named the date of first licensing and provided information concerning the total kilometers (km) driven. Kilometers per month have then been calculated as an additional quality signal - completing the vector y as discussed above. Table 1 provides the list of available advertisement information and the respective abbreviations used in the following. It also reports some descriptive statistics. 3.2 Differences in the quality distributions The assumption of internet dominance with respect to the information gathering costs implies that - in competitive equilibrium - e-commerce trade occurs over all segments, while the traditional market will lack some low-quality segments. The descriptive 16

Joint Product Signals of Quality By James E. McClure and Lee C. Spector Ball State University Muncie, Indiana September 1991 Abstract In the absence of other information about the quality of an experience

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